def test_nested_2(dictionary=nested_dictionary):
rule = df.Rule((('m', ), df.Not(('M', )), df.Not(('rr', )), df.All()))
queries = set(df.expand_rule(rule, dictionary))
queries0 = set([('m', 'MM', 'iii', 'kkkk'), ('m', 'MM', 'iii', 'uuuu'),
('m', 'RR', 'iii', 'kkkk'), ('m', 'II', 'ooo', 'ssss'),
('m', 'II', 'ooo', 'llll')])
assert queries == queries0, queries
def test_include(data=data):
fdata = df.nested_filter([df.Rule((df.All(), ('cumulative', )))], data)
data0 = {
'9b55b50c729411ea80ea42a51fad92d3': {
'cumulative':
data['9b55b50c729411ea80ea42a51fad92d3']['cumulative']
}
}
assert compare(data0, fdata)
def test_nested_lambda2(dictionary=nested_dictionary):
pattern = re.compile('^ssss$')
want = lambda key, pattern=pattern: pattern.match(key) is not None
rule = df.Rule(
(df.All(), (lambda key: len(key) == 2, ), df.All(), (want, )))
queries = set(df.expand_rule(rule, dictionary))
queries0 = set([('m', 'II', 'ooo', 'ssss')])
assert queries == queries0, (queries, queries0)
def test_not(data=data):
rules = [df.Rule((df.All(), ('daily', ), df.All()))]
fdata = df.nested_filter(rules, data)
data0 = {
'9b55b50c729411ea80ea42a51fad92d3': {
'daily': {
'2020-04-10':
data['9b55b50c729411ea80ea42a51fad92d3']['daily']
['2020-04-10'],
'2020-04-11':
data['9b55b50c729411ea80ea42a51fad92d3']['daily']['2020-04-11']
}
}
}
assert compare(data0, fdata)
def test_nested_4(dictionary=nested_dictionary):
rule = df.Rule((('m', ), ('MM', 'II'), df.All()))
queries = set(df.expand_rule(rule, dictionary))
queries0 = set([('m', 'MM', 'iii'), ('m', 'MM', 'rrr'), ('m', 'MM', 'ooo'),
('m', 'II', 'rrr'), ('m', 'II', 'ooo')])
assert queries == queries0, queries
def test_simple_single(dictionary=dictionary):
rule = df.Rule((('m', ), ))
queries = set(df.expand_rule(rule, dictionary))
print(queries)
queries0 = set([('m', )])
assert queries == queries0, (queries, queries0)
def test_invalid_key(data=data):
fdata = df.nested_filter([df.Rule((('1', )))], data)
assert not len(fdata)
def test_copy(data=data):
fdata = df.nested_filter([df.Rule((df.All(), ))], data)
assert compare(data, fdata)
def test_simple_all(dictionary=dictionary):
rule = df.Rule((df.All(), ))
queries = set(df.expand_rule(rule, dictionary))
print(queries)
queries0 = set([('m', ), ('i', ), ('r', ), ('o', )])
assert queries == queries0, queries
def test_nested_lambda(dictionary=nested_dictionary):
rule = df.Rule((df.All(), (lambda key: len(key) == 2, )))
queries = set(df.expand_rule(rule, dictionary))
queries0 = set([('m', 'MM'), ('m', 'II'), ('m', 'RR')])
assert queries == queries0, queries
def test_nested_9(dictionary=nested_dictionary):
rules = [df.Rule((df.All(), df.All(), df.All(), ('ssss', )))]
v = df.nested_filter(rules, dictionary)
assert len(v) == 1
key, = list(df.nested_keys(v))
assert key == ('m', 'II', 'ooo', 'ssss')
def test_nested_8(dictionary=nested_dictionary):
# Empty one
rule = df.Rule(('aa', ))
queries = set(df.expand_rule(rule, dictionary))
assert not queries
def test_nested_7(dictionary=nested_dictionary):
# Empty one
rule = df.Rule((df.All(), df.All(), df.All(), df.All(), ('ssss', )))
queries = set(df.expand_rule(rule, dictionary))
assert not queries
def test_nested_6(dictionary=nested_dictionary):
rule = df.Rule((df.All(), ('MM', 'RR'), df.All(), ('kkkk', 'uuuu')))
queries = set(df.expand_rule(rule, dictionary))
queries0 = set([('m', 'MM', 'iii', 'kkkk'), ('m', 'MM', 'iii', 'uuuu'),
('m', 'RR', 'iii', 'kkkk')])
assert queries == queries0, queries
def test_nested_5(dictionary=nested_dictionary):
# Four level where last is 's'
rule = df.Rule((df.All(), df.All(), df.All(), ('ssss', )))
queries = set(df.expand_rule(rule, dictionary))
queries0 = set([('m', 'II', 'ooo', 'ssss')])
assert queries == queries0, queries
